Metabolic Syndrome in Patients with Depressive Disorder: A Cross-sectional Study.

BACKGROUND

Depression not only fosters the development of metabolic syndrome through behavioral, physiological, genetic, and treatment-related factors, but it also doubles the risk of experiencing metabolic syndrome. The objectives were to assess the sociodemographic and clinical profile of patients with depressive disorder, to assess the various metabolic parameters of metabolic syndrome in patients with depressive disorder, and to study the association between the severity of depression and metabolic syndrome.

METHODS

A cross-sectional study was conducted among patients diagnosed with depression (n = 160) attending the Psychiatry outpatient department of a tertiary healthcare facility in Puducherry. The Hamilton Depression Rating Scale (HAM-D) and modified National Cholesterol Education Program-Adult Treatment Panel-III (NCEP ATP-III) criteria were used to assess the severity of depression and diagnose metabolic syndrome, respectively.

RESULTS

The mean age at onset of depression was 31.4 years (+11.3); the duration of depression was 41.2 months (+32.5); and the severity of depression as assessed using the HAM-D was 17.9 (+6.3). The results showed that 27.5% of patients had metabolic syndrome. Factors associated with higher rates of metabolic syndrome included increasing age, female gender (79.5%), being single (25.0%), belonging to upper socioeconomic class (65.9%), non-Hindu religion (20.5%), and urban residence (72.7%) ( < .05). Patients with metabolic syndrome had later onset (36.4 years) and longer duration (51.6 months) of depression, more severe symptoms (18.2), and were more likely to have recurrent depressive disorder or dysthymia (88.6%) ( < .05). Furthermore, the current use of psychotropic medications (59.1%) and obesity (93.2%) were significantly associated with metabolic syndrome ( < .05).

CONCLUSION

This study reveals a high prevalence of metabolic syndrome among patients with depressive disorders linked to factors such as age, gender, marital status, socioeconomic status, religion, and urban residence. Integrated care approaches, including comprehensive screening and targeted interventions, are crucial for improving both mental and metabolic health outcomes.